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Gaseous emissions from agricultural biomass combustion: a prediction model
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org
Citation: Paper number 131594309, 2013 Kansas City, Missouri, July 21 - July 24, 2013. (doi: http://dx.doi.org/10.13031/aim.20131594309) @2013
Authors: Sébastien Fournel, Bernard Marcos, Stéphane Godbout, Michèle Heitz
Keywords: Biomass combustion gasification gaseous emissions prediction model chemical equilibrium Gibbs free energy.
Abstract. As the price of the fossil energy resources and the need to reduce the environmental impacts from energy use increase, biomass fuels have regained interest from Quebecâ€™s agricultural sector. Producing and burning energy crops at the farm have become strategies to diversify incomes and decrease dependency to fossil fuels. However, the current absence of emission factors for solid fuel combustion does not allow a sustainable development for energy purposes. Besides, the variety of existing furnaces and biomasses complicates the establishment of such reference values. In order to quantify emissions (CO, CO2, NOx, SO2, CH4, NH3 and HCl) from on-farm combustion of different agricultural biomasses (short-rotation willow, switchgrass, reed canary grass, etc.), a prediction model was established based on the calculation of chemical equilibrium of reactive multicomponent systems. Under constant temperature and pressure, this technique has been judged as relevant for the prediction of product compositions considering inlet conditions in several operations and chemical processes, particularly gasification. The model was first established for wood gasification to be able to compare and validate its results with those of existing models from the literature using the same original data. The model was then adapted to biomass combustion and calibrated with recent results from combustion tests held in the province of Quebec. The preliminary results of the prediction model using data from past combustion experiments with wood, willow and switchgrass revealed good agreement between both measured and predicted values. Other simulation tests are required to increase accuracy of the model.
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